tencent cloud


Implementing Exponential Backoff to Deal with Service Frequency

Last updated: 2024-01-11 16:31:22

    Suggestions for Dealing with Exceptions

    If exceptional errors occur when you call KMS APIs to send requests from your application to the remote KMS server, you can deal with the errors as suggested below:
    Cancel the call: if an error shows that the failure is not temporary and persists after several re-executions, you need to terminate or cancel the application call and report the error.
    Try again immediately: if an uncommon error is returned, for example, network packets are damaged during transfer but still sent, in this case, you can try again immediately.
    Increase delays between re-executions: if an error is generally caused by connections, it indicates that the server is busy and needs to clear the loads first. You can try again in a while in such cases.
    The following paragraphs introduce how to increase delays between re-executions. The delay can be gradually increased or scheduled (by implementing exponential backoff). As the frequency of KMS API calls is limited, you can increase delays between re-executions to avoid errors caused by high frequency.

    Exponential Backoff


    // Gradually increase re-execution delays
    InitDelayValue = 100
    For(Retries = 0; Retries < MAX_RETRIES; Retries = Retries+1)
    wait for (2^Retries * InitDelayValue) milliseconds
    Status = KmsApiRequest()
    IF Status == SUCCESS
    BREAK // Succeeded, stop calling the API again.
    CONTINUE // Failed due to throttling or server busy, try again.
    BREAK // another error occurs, stop calling the API again.
    END IF


    Python: implement exponential backoff for frequency errors in KMS API calls to Encrypt
    # -*- coding: utf-8 -*-
    import base64
    import math
    import time
    from tencentcloud.common import credential
    from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
    from tencentcloud.common.profile.client_profile import ClientProfile
    from tencentcloud.common.profile.http_profile import HttpProfile
    from tencentcloud.kms.v20190118 import kms_client, models
    def KmsInit(region="ap-guangzhou", secretId="", secretKey=""):
    credProfile = credential.Credential(secretId, secretKey)
    client = kms_client.KmsClient(credProfile, region)
    return client
    except TencentCloudSDKException as err:
    return None
    def BackoffFunction(RetryCount):
    InitDelayValue = 100
    DelayTime = math.pow(2, RetryCount) * InitDelayValue
    return DelayTime
    if __name__ == '__main__':
    # User-defined parameters
    secretId = "replace-with-real-secretId"
    secretKey = "replace-with-real-secretKey"
    region = "ap-guangzhou"
    keyId = "replace-with-realkeyid"
    plaintext = "abcdefg123456789abcdefg123456789abcdefg"
    Retries = 0
    MaxRetries = 10
    client = KmsInit(region, secretId, secretKey)
    req = models.EncryptRequest()
    req.KeyId = keyId
    req.Plaintext = base64.b64encode(plaintext)
    while Retries < MaxRetries:
    Retries += 1
    rsp = client.Encrypt(req) # Call the API `Encrypt`
    print 'plaintext: ',plaintext,'CiphertextBlob: ',rsp.CiphertextBlob
    except TencentCloudSDKException as err:
    if err.code == 'InternalError' or err.code == 'RequestLimitExceeded':
    if Retries == MaxRetries:
    time.sleep(BackoffFunction(Retries + 1))
    except Exception as err:
    To deal with other specific errors, you can directly modify the content of the statement except.
    You can customize the schedule policy based on your code logic and business policy to set the optimal initial delay value (InitDelayValue) and the number of retries (Retries), preventing your business from being affected by a too-low or too-high threshold.
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